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About CataractNet An Automated Cataract Detection System Using Deep Learning For Fundus Images
This document describes a research paper that proposes a new deep neural network called CataractNet for automated detection of cataracts using fundus images. CataractNet is designed and tuned to have small kernels, fewer parameters and layers to reduce computational cost and run time compared to other pre-trained CNN models. The network is trained on a dataset of over 4,000 fundus images and achieves an average accuracy of 99.13% for cataract detection, outperforming other state-of-the-art methods.
Detailed Information
| Author: | ['Faizan Ammar'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 10 |
| Language: | English |
| Format: | |
| Price: | FREE |
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